ArticleJournal of applied phycology2016
Coupling a simple irradiance description to a mechanistic growth model to predict algal production in industrial-scale solar-powered photobioreactors.
Article in Journal of applied phycology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Microalgae and cyanobacteria modeling in water resource recovery facilities: A critical review.Water research X · 2019Review
- Minimising losses to predation during microalgae cultivation.Journal of applied phycology · 2017Article
- Physiology limits commercially viable photoautotrophic production of microalgal biofuels.Journal of applied phycology · 2017Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Various innovative photobioreactor designs have been proposed to increase production of algae-derived biomass. Computer models are often employed to test these designs prior to construction. In the drive to optimise conversion of light energy to biomass, efforts to model the profile of irradiance levels within a microalgal culture can lead to highly complex descriptions which are computationally demanding. However, there is a risk that this effort is wasted if such optic models are coupled to overly simplified descriptions of algal physiology. Here we demonstrate that a suitable description of microalgal physiology is of primary significance for modelling algal production in photobioreactors. For the first time, we combine a new and computationally inexpensive model of irradiance to a mechanistic description of algal growth and test its applicability to modelling biofuel production in an advanced photobioreactor system. We confirm the adequacy of our approach by comparing the predictions of the model against published experimental data collected over a 2 ½-year period and demonstrate the effectiveness of the mechanistic model in predicting long-term production rates of bulk biomass and biofuel feedstock components at a commercially relevant scale. Our results suggest that much of the detail captured in more complicated irradiance models is indeed wasted as the critical limiting procedure is the physiological description of the conversion of light energy to biomass.
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Registered trials
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